Rtweet

an Rfun demonstration

https://www.tidytextmining.com/

load libraries

library(rtweet)
library(tidyverse)
library(tidytext)
library(wordcloud2)

Get Tweets

search_tweets

tweet_collection <- search_tweets("marchmadness", n=1000, lang = "en")

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tweet_collection <- tweet_collection %>% 
  filter(is_retweet == "FALSE")
tweet_collection

Tokenize tweets

tweets_by_tweeter <- tweet_collection %>% 
  group_by(screen_name) %>% 
  mutate(line = row_number()) %>% 
  ungroup()

tweets_by_tweeter %>% 
  count(screen_name, sort = TRUE)

glimpse(tweets_by_tweeter)

Rows: 466
Columns: 91
$ user_id                 <chr> "935344574", "409272386", "777159887495147525", "326586556", "847035646376132608", "...
$ status_id               <chr> "1324087223030079489", "1324084896235724807", "1324082875323584512", "13240821973898...
$ created_at              <dttm> 2020-11-04 20:32:48, 2020-11-04 20:23:34, 2020-11-04 20:15:32, 2020-11-04 20:12:50,...
$ screen_name             <chr> "Indychick31", "amybuddy45", "MegaOmegaNes", "NickRevell317", "ckylaurie", "LancePot...
$ text                    <chr> "@NickRevell317 @marchmadness Feels more like Pacers/Knicks ECF", "@TowsonTigers @To...
$ source                  <chr> "Twitter for iPhone", "Twitter for Android", "Twitter for iPhone", "Twitter for Andr...
$ display_text_width      <dbl> 33, 38, 72, 40, 66, 216, 26, 119, 230, 237, 238, 197, 66, 29, 137, 41, 69, 202, 53, ...
$ reply_to_status_id      <chr> "1324082197389844480", "1323643115266256897", "1324078964911071232", "13240808189989...
$ reply_to_user_id        <chr> "326586556", "28380954", "32463369", "326586556", "88001676", NA, "3002054440", NA, ...
$ reply_to_screen_name    <chr> "NickRevell317", "TowsonTigers", "SouthlandSports", "NickRevell317", "notaxation", N...
$ is_quote                <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, F...
$ is_retweet              <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, ...
$ favorite_count          <int> 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 2, 5, 0, 3, 2, 0, 0, 1, 38, 0, 0, 1, 1,...
$ retweet_count           <int> 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 1, 0, 1, ...
$ quote_count             <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ reply_count             <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ hashtags                <list> [NA, NA, NA, NA, NA, <"MarchMadness", "Vote2020", "Vote", "Election2020", "Election...
$ symbols                 <list> [NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
$ urls_url                <list> [NA, NA, NA, NA, NA, NA, NA, "twitter.com/marchmadness/s…", NA, NA, NA, NA, NA, NA,...
$ urls_t.co               <list> [NA, NA, NA, NA, NA, NA, NA, "https://t.co/7dpNdQUJub", NA, NA, NA, NA, NA, NA, NA,...
$ urls_expanded_url       <list> [NA, NA, NA, NA, NA, NA, NA, "https://twitter.com/marchmadness/status/1321453097848...
$ media_url               <list> [NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "h...
$ media_t.co              <list> [NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "h...
$ media_expanded_url      <list> [NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "h...
$ media_type              <list> [NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "p...
$ ext_media_url           <list> [NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "h...
$ ext_media_t.co          <list> [NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "h...
$ ext_media_expanded_url  <list> [NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "h...
$ ext_media_type          <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ mentions_user_id        <list> [<"326586556", "202416362">, <"28380954", "320568857", "312784438", "611927090", "7...
$ mentions_screen_name    <list> [<"NickRevell317", "marchmadness">, <"TowsonTigers", "Towson_MBB", "Towson_WBB", "T...
$ lang                    <chr> "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", ...
$ quoted_status_id        <chr> NA, NA, NA, NA, NA, NA, NA, "1321453097848393730", NA, NA, NA, NA, NA, NA, NA, NA, N...
$ quoted_text             <chr> NA, NA, NA, NA, NA, NA, NA, "Four. More. Weeks. \U0001f64c https://t.co/20rsOT5FVL",...
$ quoted_created_at       <dttm> NA, NA, NA, NA, NA, NA, NA, 2020-10-28 14:05:44, NA, NA, NA, NA, NA, NA, NA, NA, NA...
$ quoted_source           <chr> NA, NA, NA, NA, NA, NA, NA, "Twitter Web App", NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
$ quoted_favorite_count   <int> NA, NA, NA, NA, NA, NA, NA, 1244, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
$ quoted_retweet_count    <int> NA, NA, NA, NA, NA, NA, NA, 227, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
$ quoted_user_id          <chr> NA, NA, NA, NA, NA, NA, NA, "202416362", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
$ quoted_screen_name      <chr> NA, NA, NA, NA, NA, NA, NA, "marchmadness", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ quoted_name             <chr> NA, NA, NA, NA, NA, NA, NA, "NCAA March Madness", NA, NA, NA, NA, NA, NA, NA, NA, NA...
$ quoted_followers_count  <int> NA, NA, NA, NA, NA, NA, NA, 1420876, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
$ quoted_friends_count    <int> NA, NA, NA, NA, NA, NA, NA, 816, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
$ quoted_statuses_count   <int> NA, NA, NA, NA, NA, NA, NA, 29878, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
$ quoted_location         <chr> NA, NA, NA, NA, NA, NA, NA, "", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ quoted_description      <chr> NA, NA, NA, NA, NA, NA, NA, "The official NCAA March Madness destination for all thi...
$ quoted_verified         <lgl> NA, NA, NA, NA, NA, NA, NA, TRUE, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
$ retweet_status_id       <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_text            <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_created_at      <dttm> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
$ retweet_source          <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_favorite_count  <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_retweet_count   <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_user_id         <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_screen_name     <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_name            <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_followers_count <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_friends_count   <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_statuses_count  <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_location        <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_description     <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ retweet_verified        <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ place_url               <chr> NA, NA, "https://api.twitter.com/1.1/geo/id/ebf78e870cecf27c.json", "https://api.twi...
$ place_name              <chr> NA, NA, "Nacogdoches", "Indiana", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
$ place_full_name         <chr> NA, NA, "Nacogdoches, TX", "Indiana, USA", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N...
$ place_type              <chr> NA, NA, "city", "admin", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "admin"...
$ country                 <chr> NA, NA, "United States", "United States", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA...
$ country_code            <chr> NA, NA, "US", "US", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "US", NA, NA...
$ geo_coords              <list> [<NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <N...
$ coords_coords           <list> [<NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <NA, NA>, <N...
$ bbox_coords             <list> [<NA, NA, NA, NA, NA, NA, NA, NA>, <NA, NA, NA, NA, NA, NA, NA, NA>, <-94.70422, -9...
$ status_url              <chr> "https://twitter.com/Indychick31/status/1324087223030079489", "https://twitter.com/a...
$ name                    <chr> "Indychick", "Amy Pullifrone", "Leon", "Nick Revell", "Ckylaurie", "Lance Potts", "\...
$ location                <chr> "", "Maryland", "Deep Deep Deep East, Tx", "Indianapolis, Indiana", "Winnipeg, Manit...
$ description             <chr> "In 49 states it’s just basketball... but THIS...is INDIANA", "A wife, mother, daugh...
$ url                     <chr> NA, NA, NA, NA, NA, NA, NA, "https://t.co/3vvVhjYDZN", "https://t.co/f4Ba651McX", "h...
$ protected               <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, ...
$ followers_count         <int> 420, 259, 222, 2000, 41, 284, 147, 2694, 63, 63, 63, 63, 1, 440, 1963, 67, 319, 1158...
$ friends_count           <int> 750, 2432, 419, 1765, 149, 462, 255, 81, 270, 270, 270, 270, 174, 2367, 820, 163, 52...
$ listed_count            <int> 25, 12, 1, 24, 1, 28, 0, 53, 0, 0, 0, 0, 0, 18, 4, 0, 2, 64, 0, 12, 0, 0, 66, 453, 0...
$ statuses_count          <int> 59228, 4484, 3123, 102132, 1667, 19894, 5021, 11340, 2309, 2309, 2309, 2309, 41, 771...
$ favourites_count        <int> 54457, 2036, 10867, 314, 1745, 16379, 18108, 4472, 240, 240, 240, 240, 22, 20579, 66...
$ account_created_at      <dttm> 2012-11-08 20:19:08, 2011-11-10 14:18:09, 2016-09-17 14:58:50, 2011-06-30 04:41:02,...
$ verified                <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, ...
$ profile_url             <chr> NA, NA, NA, NA, NA, NA, NA, "https://t.co/3vvVhjYDZN", "https://t.co/f4Ba651McX", "h...
$ profile_expanded_url    <chr> NA, NA, NA, NA, NA, NA, NA, "https://pickscity.com/shop/laker_crazy-daily/", "http:/...
$ account_lang            <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
$ profile_banner_url      <chr> "https://pbs.twimg.com/profile_banners/935344574/1525299925", "https://pbs.twimg.com...
$ profile_background_url  <chr> "http://abs.twimg.com/images/themes/theme1/bg.png", "http://abs.twimg.com/images/the...
$ profile_image_url       <chr> "http://pbs.twimg.com/profile_images/2825347118/66387d87e20f42982aad1ee2f6fc4e84_nor...
$ line                    <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, ...

"Because we have kept text such as hashtags and usernames in the dataset, we can’t use a simple anti_join() to remove stop words. Instead, we can take the approach shown in the filter() line that uses str_detect() from the stringr package. – https://www.tidytextmining.com/twitter.html

tweets_tokenized <- tweets_by_tweeter %>% 
  select(text, screen_name, line) %>% 
  unnest_tokens(word, text, token = "tweets") %>%
  filter(!word %in% stop_words$word,
         !word %in% str_remove_all(stop_words$word, "'"),
         str_detect(word, "[a-z]")) 

Using `to_lower = TRUE` with `token = 'tweets'` may not preserve URLs.

tweets_tokenized

stop words

head(stopwordslangs)

tweets_tokenized %>% 
  count(word, sort = TRUE, name = "freq") %>% 
  filter(!str_detect(word, "^\\@")) %>% 
  anti_join(stopwordslangs)           # anti_join(tidytext::get_stopwords())

Joining, by = "word"

Word frequencies

Calculate word frequency

frequency <- tweets_tokenized %>% 
  group_by(screen_name) %>% 
  count(word, sort = TRUE) %>% 
  left_join(tweets_tokenized %>% 
              group_by(screen_name) %>% 
              summarise(total = n())) %>%
  mutate(freq = n/total)

`summarise()` ungrouping output (override with `.groups` argument)
Joining, by = "screen_name"

frequency

"This is a nice and tidy data frame but we would actually like to plot those frequencies on the x- and y-axes of a plot, so we will need to use spread() from tidyr make a differently shaped data frame. – https://www.tidytextmining.com/twitter.html

pivot_wider

frequency <- frequency %>% 
  select(screen_name, word, freq) %>% 
  pivot_wider(names_from = screen_name, values_from = freq) #, values_fill = 0)

frequency

viz it

tweets_tokenized %>% 
  # group_by(screen_name) %>% 
  count(word, sort = TRUE, name = "freq") %>% 
  filter(!str_detect(word, "^\\@")) %>% 
  anti_join(stopwordslangs)  %>% 
  wordcloud2()

Joining, by = "word"

tweets_tokenized %>% 
  count(word, sort = TRUE, name = "freq") %>% 
  filter(!str_detect(word, "^\\@")) %>% 
  slice_head(n = 30) %>% 
  ggplot(aes(freq, fct_reorder(word, freq))) +
  geom_col()

tweets_tokenized %>% 
  count(word, sort = TRUE, name = "freq") %>% 
  anti_join(stopwordslangs) %>% 
  filter(!str_detect(word, "^\\@")) %>% 
  slice_head(n = 30) %>% 
  ggplot(aes(freq, fct_reorder(word, freq))) +
  geom_col()

Joining, by = "word"

ggplot(frequency, aes(LouInPain, Dukeballnation)) +
  geom_jitter(alpha = 0.1, size = 2.5, width = 0.25, height = 0.25) +
  geom_text(aes(label = word), check_overlap = TRUE, vjust = 1.5) +
  scale_x_log10(labels = scales::percent_format()) +
  scale_y_log10(labels = scales::percent_format()) +
  geom_abline(color = "firebrick")

# fs::dir_create("images")
# ggsave("images/dukeball.png")

# "CBBCent1" | screen_name == "Adam_Bradford1
# marchmadness  TheAndyKatz

ggplot(frequency, aes(marchmadness, TheAndyKatz)) +
  geom_jitter(alpha = 0.1, size = 2.5, width = 0.25, height = 0.25) +
  geom_text(aes(label = word), check_overlap = TRUE, vjust = 1.5) +
  scale_x_log10(labels = scales::percent_format()) +
  scale_y_log10(labels = scales::percent_format()) +
  geom_abline(color = "firebrick")

Word Usage

tweets_by_tweeter %>% 
  summarise(min_date = min(created_at), max_date = max(created_at))

word_ratios <- tweets_tokenized %>%
  # filter(screen_name == "CBBCent1" | screen_name == "Adam_Bradford14") %>%
  filter(screen_name == "LouInPain" | screen_name == "Dukeballnation") %>% 
  filter(!str_detect(word, "^@")) %>%
  count(word, screen_name) %>%
  group_by(word) %>%
  filter(sum(n) >= 2) %>%
  ungroup() %>%
  pivot_wider(names_from = screen_name, values_from = n, values_fill = 0) %>%
  mutate_if(is.numeric, list(~(. + 1) / (sum(.) + 1))) %>%
  mutate(logratio = log(LouInPain / Dukeballnation)) %>%
  arrange(desc(logratio))

Error: Problem with `mutate()` input `logratio`.
x object 'LouInPain' not found
i Input `logratio` is `log(LouInPain/Dukeballnation)`.
Run `rlang::last_error()` to see where the error occurred.

equal usage

word_ratios %>% 
  arrange(abs(logratio))

word_ratios %>%
  group_by(logratio < 0) %>%
  top_n(15, abs(logratio)) %>%
  ungroup() %>%
  mutate(word = reorder(word, logratio)) %>%
  ggplot(aes(word, logratio, fill = logratio < 0)) +
  geom_col() + #show.legend = FALSE) +
  coord_flip() +
  ylab("log odds ratio (CCBCent1/Adam_Bradford14)") +
  scale_fill_discrete(name = "", labels = c("LouInPain", "Dukeballnation"))

Favorites and retweets

https://www.tidytextmining.com/twitter.html#favorites-and-retweets

Changes in word use

https://www.tidytextmining.com/twitter.html#changes-in-word-use

Term Document Matrix

{r}
# dtm <- DocumentTermMatrix(docs) 

dtm2 <- TermDocumentMatrix(corpus)
m <- as.matrix(dtm2)
v <- sort(rowSums(m),decreasing=TRUE)
d <- data.frame(word = names(v),freq=v)

d <- d %>% 
  slice(2:200)

https://www.tidytextmining.com/tfidf.html#the-bind_tf_idf-function

tweet_words <- tweets_by_tweeter %>% 
  select(screen_name, text, status_id, user_id) %>%  
  unnest_tokens(word, text, token = "tweets") %>% 
  filter(!str_detect(word, "^\\@")) %>%
  filter(!str_detect(word, "^http")) %>%
  anti_join(stopwordslangs)  %>% 
  count(word, tweeter = screen_name, sort = TRUE)

Using `to_lower = TRUE` with `token = 'tweets'` may not preserve URLs.
Joining, by = "word"

tweet_words

total_words <- tweet_words %>%
  group_by(tweeter) %>%
  summarize(total = sum(n)) %>% 
  arrange(-total)

`summarise()` ungrouping output (override with `.groups` argument)

total_words

tweet_words <- left_join(tweet_words, total_words)

Joining, by = "tweeter"

tweet_words

tweet_words %>% 
  bind_tf_idf(word, tweeter, n)

tweet_words %>% 
  bind_tf_idf(word, tweeter, n) %>% 
  arrange(desc(tf_idf)) %>% 
  mutate(word = factor(word, levels = rev(unique(word)))) %>% 
  filter(n > 2) %>% 
  # group_by(tweeter) %>% 
  # top_n(2) %>% 
  # ungroup() %>% 
  ggplot(aes(word, tf_idf)) +
  geom_col() +
  facet_wrap(~ tweeter) +
  coord_flip()

Resource list

• http://www.sthda.com/english/wiki/text-mining-and-word-cloud-fundamentals-in-r-5-simple-steps-you-should-know

• http://antonio-ferraro.eu.pn/word-clouds-in-r-packages-wordcloud2-and-tm/

• https://jrnold.github.io/qss-tidy/discovery.html#textual-data

• https://rstudio-pubs-static.s3.amazonaws.com/31867_8236987cf0a8444e962ccd2aec46d9c3.html

• of less use

  • http://www.cookbook-r.com/Manipulating_data/Converting_between_data_frames_and_contingency_tables/
  • https://www.r-bloggers.com/how-to-get-the-frequency-table-of-a-categorical-variable-as-a-data-frame-in-r/
  • https://www.quora.com/How-do-I-get-a-frequency-count-based-on-two-columns-variables-in-an-R-dataframe
  • https://www.quora.com/How-do-you-create-a-corpus-from-a-data-frame-in-R